Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing.

Yonghui Wu,Liwei Wang,Min Jiang,Hui Nian,Hua Xu,Jeremy L Warner,Joshua C Denny,Ping Yang,Xianglin Du,Qingxia Chen,Jun Xu,Qi Dai,Hongfang Liu

doi:10.1200/cci.19.00001

Abstract

PURPOSEDrug development is becoming increasingly expensive and time consuming. Drug repurposing is one potential solution to accelerate drug discovery. However, limited research exists on the use of electronic health record (EHR) data for drug repurposing, and most published studies have been conducted in a hypothesis-driven manner that requires a predefined hypothesis about drugs and new indications. Whether EHRs can be used to detect drug repurposing signals is not clear. We want to demonstrate the feasibility of mining large, longitudinal EHRs for drug repurposing by detecting candidate noncancer drugs that can potentially be used for the treatment of cancer.PATIENTS AND METHODSBy linking cancer registry data to EHRs, we identified 43,310 patients with cancer treated at Vanderbilt University Medical Center (VUMC) and 98,366 treated at the Mayo Clinic. We assessed the effect of 146 noncancer drugs on cancer survival using VUMC EHR data and sought to replicate significant associations (false discovery rate < .1) using the identical approach with Mayo Clinic EHR data. To evaluate replicated signals further, we reviewed the biomedical literature and clinical trials on cancers for corroborating evidence.RESULTSWe identified 22 drugs from six drug classes (statins, proton pump inhibitors, angiotensin-converting enzyme inhibitors, β-blockers, nonsteroidal anti-inflammatory drugs, and α-1 blockers) associated with improved overall cancer survival (false discovery rate < .1) from VUMC; nine of the 22 drug associations were replicated at the Mayo Clinic. Literature and cancer clinical trial evaluations also showed very strong evidence to support the repurposing signals from EHRs.CONCLUSIONMining of EHRs for drug exposure–mediated survival signals is feasible and identifies potential candidates for antineoplastic repurposing. This study sets up a new model of mining EHRs for drug repurposing signals.

Highlights

Cancer drug development is increasingly expensive and time consuming
We identified 22 drugs from six drug classes associated with improved overall cancer survival from Vanderbilt University Medical Center (VUMC); nine of the 22 drug associations were replicated at the Mayo Clinic
This study sets up a new model of mining electronic health record (EHR) for drug repurposing signals

Summary

Introduction

Cancer drug development is increasingly expensive and time consuming. The development of a new drug is estimated to cost $648 million[1] to $2.5 billion[2] and takes an average of 9 to 12 years before market availability.[3] The drug development success rate is less than 8% because of lack of efficacy, excess toxicity, declining research and development, cost of commercialization, and payer influence.[4] Cancer drugs are the top sellers among all Food and Drug Administration– approved therapies.[5] many new cancer therapeutics are in development, new methods to accelerate drug discovery are needed. A recent study reported that the discovery of new indications of existing drugs accounts for 20% of new drug products.[8]

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